#!/bin/sh
# coding=utf-8


import numpy as np
import urllib
from sklearn import metrics
from sklearn.naive_bayes import GaussianNB


labes = ['good', 'bad']
url = "http://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data"

class Bayes:

    def text_parse(self):
        model = GaussianNB()
        model.fit(x,y)
        print(model)

        # predications
        print(metrics.classification_report(expected,predicted))
        print(metrics.confusion_matrix(expected,predicted))


